The present invention generally relates to image potential control systems and image forming apparatuses, and more particularly to an image potential control system which employs neural control to control an image potential (dark portion potential and bright portion potential) on a photosensitive body of an image forming apparatus such as an optical (or laser) printer, a copying machine and a facsimile machine which use the electrophotography technique, and to an image forming apparatus having such an image potential control system.
Conventionally, in image forming apparatuses which use the electrophotography technique, the precision of parts forming the apparatus, the characteristic values at the time of the assembling and the like are managed with respect to process conditions, so as to stably realize images having a high quality. In addition, the process conditions are optimized by detecting controlled variables with respect to the property (quantity of state) and the manipulated variable of each process controller and carrying out a feedback control based on the detected controlled variables.
On the other hand, a neuro-control using a neural network is known. A Japanese Laid-Open Patent Application no.3-167655 shows an example of such a neuro-control. The neural network first searches for a fine solution by giving a degree of freedom in a state where the restricting conditions are not strict. Then, the neural network gradually makes the restricting conditions more strict so as to obtain a solution which is fine to a certain extent and satisfies the restricting conditions.
Accordingly, proposals have been made to employ the neuro-control of the neural network for controlling the process conditions of the image forming apparatus.
However, in order to stabilize the image quality of the image forming apparatus, there are simply too many factors which affect the image quality when the entire process of the image forming apparatus is taken into account. As a result, it is impossible to carry out an established control, and the processes of the image forming apparatus must constantly be adjusted by an expert.
In addition, when the neuro-control is employed, the variation between the characteristic of a particular model of the image forming apparatus at the time when the learning data for the neuro-control are measured and the characteristic of each individual product of this particular model becomes a big problem. In other words, when carrying out the neuro-control, the use of the limited learning data for all of the products introduces differences in the performances of the individual products. For example, it is extremely difficult to constantly control the image potential on the photosensitive body to the optimum state in each of the individual products.